Background
Aggressive non-Hodgkin lymphoma (aNHL) is the most common lymphoid malignancy, frequently affecting older adults.1 Treatment requires intensive chemoimmunotherapy, which offers the potential for durable remissions.2,3 However, most older patients will experience grade ≥3 adverse events, often leading to substantial toxicities and increased health care utilization.4
Older adults have unique characteristics that impact their tolerability of chemoimmunotherapy and quality of life (QoL) trajectory, including comorbidities, altered physical and cognitive function, and impaired metabolism.5,6 Despite this, no studies have examined longitudinal QoL and other patient-reported outcomes (PROs) in this population. Furthermore, our understanding of how therapy impacts QoL or which factors influence QoL trajectories remains limited.
Prior research has shown that geriatric assessment (GA) and the Vulnerable Elders Survey-13 (VES-13) are both associated with survival in patients with lymphoma.7–9 The GA formally evaluates older patients’ functional status, comorbidities, medications, psychological state, social support, and nutrition,7 offering insights into patient frailty and toxicity risk, particularly in solid tumors.10 The VES-13 is a brief patient-reported instrument used to identify older adults at risk for frailty.11
This study aimed to examine longitudinal PROs in older adults with aNHL receiving chemoimmunotherapy and identify factors associated with QoL trajectory. We hypothesized that patients would experience longitudinal improvements in QoL and that frailty status would be associated with worse longitudinal QoL.
Patients and Methods
Study Population
Eligible patients were required to be ≥65 years of age at the time of treatment initiation, have a diagnosis of aNHL as defined by the 2016 revision of the WHO classification of lymphoid neoplasms,12 and be able to read and understand questions in English, independently or with translator assistance. Patients could enroll up to cycle 1, day 8 of first-line therapy. Patients with significant psychiatric disorders or other comorbid diseases which the primary oncologist believed prohibited informed consent were excluded.
Study Design
We conducted a longitudinal study of older adults with aNHL receiving chemoimmunotherapy between September 2020 and January 2023 at 2 academic centers or their community affiliates. We approached consecutively eligible patients for study participation after obtaining permission from treating oncologists. Willing participants provided written informed consent and completed baseline questionnaires at enrollment. We administered self-reported measures at baseline; 6, 12, 18, and 24 weeks post–therapy initiation; and 1 year post–therapy initiation (±1 week). Patients with disease progression or who changed therapy for insufficient response continued on study. This study was approved by the Dana-Farber/Harvard Cancer Center Institutional Review Board.
Patient-Reported Measures
Sociodemographic and Clinical Characteristics
At baseline, patients completed demographic questionnaires detailing their age, sex, race, ethnicity, marital status, income, religion, and education level. We reviewed patients’ electronic medical records (EMRs) to obtain information on cancer diagnosis, date of diagnosis, date of treatment initiation, treatment regimen, ECOG performance status (PS), cancer stage, baseline laboratory parameters closest to the date of diagnosis (eg, lactate dehydrogenase [LDH]), albumin), and Charlson comorbidity index (CCI) score (excluding their lymphoma).13 We determined patients’ age-adjusted International Prognostic Index (aa-IPI) score, a validated index for prognosis.14
Quality of Life
We used the Functional Assessment of Cancer Therapy-Lymphoma (FACT-Lym) to assess patients’ QoL. The FACT-Lym is a 42-item measure comprising 4 subscales that evaluate well-being across physical, functional, emotional, and social domains over the preceding week. Scores range from 0 to 168, with higher scores indicating better QoL.15 The minimally clinically important difference (MCID) is 6.5 to 11.2.16,17 To maximize sensitivity for detecting changes over time, we used an MCID of 6.5 to define clinically significant improvement, stability, or worsening.
Physical Symptom Burden
We used a modified version of the self-administered revised Edmonton Symptom Assessment System (ESAS-r) to assess patients’ symptoms. The ESAS-r measures pain, fatigue, drowsiness, nausea, appetite, dyspnea, and well-being over the previous 7 days.18 We added insomnia and difficulty swallowing, as these are prevalent symptoms in patients with cancer.19,20 Each symptom is scored on a scale from 0 to 10, where 0 indicates absence of symptoms and 10 indicates the worst possible severity. The total score ranges from 0 to 90, with higher scores reflecting greater symptom burden. An MCID of 3 was used to denote clinically significant improvement, based on prior studies.18
Psychological Distress
We used the Hospital Anxiety and Depression Scale (HADS) to assess participants’ anxiety and depression symptoms. The HADS is a 14-item questionnaire consisting of two 7-item subscales that evaluate anxiety and depression symptoms over the preceding week. It has demonstrated strong psychometric properties in oncology. Scores on each subscale range from 0 to 21, with a cutoff of ≥8 denoting clinically significant anxiety or depression.21 The HADS subscales can also be evaluated continuously, with higher scores reflecting worse psychological distress.22
Frailty Assessment
Geriatric Assessment
At baseline, a medical oncologist (P.C. Johnson) and research assistant conducted the Fondazione Italiana Linfomi (FIL) GA, based on previous studies of older patients with diffuse large B-cell lymphoma (DLBCL). The FIL GA incorporates age, comorbidity score, activities of daily living, and instrumental activities of daily living to categorize patients as fit, unfit, or frail.7,8,23
Vulnerable Elders Survey-13
At baseline, we administered the VES-13, a self-administered survey consisting of 1 item for age and 12 additional items evaluating self-related health, functional capacity, and physical performance. Studies using the VES-13 have demonstrated its ability to predict functional decline and mortality. A score of ≥3 indicates vulnerability in older adults.9,11
Clinical Outcomes
We abstracted information from the EMR on the presence and grade of nonhematologic toxicities,24 dose reductions, frequency and dates of treatment interruptions, response to treatment, duration of follow-up, and survival. We calculated rates of grade 3–5 nonhematologic toxicities, dose reductions, treatment interruptions (defined as a delay of >3 days in a cycle, based on prior work25), and early therapy cessation during initial treatment. Toxicities were graded using the CTCAE version 5.0. For health care utilization, we recorded the frequency and dates of hospitalizations and ICU admissions within the first 6 months following treatment initiation. Treatment-related mortality was defined as the percentage of patients who died during treatment from therapy-related causes, as determined through EMR review.
Statistical Analysis
Descriptive statistics were used to summarize patients’ sociodemographic and clinical characteristics, baseline PROs, rates of toxicities, dose reductions, treatment interruptions, and early treatment cessation. Best responses to treatment and occurrences of relapse or progression were determined through EMR review. In cases where response was not documented, a medical oncologist (P.C. Johnson) determined response according to the Lugano criteria.26 We calculated the percentage of patients alive at 6 months and 1 year after treatment initiation. Overall survival (OS) and progression-free survival (PFS) were calculated using the Kaplan-Meier method. OS was defined as the time from treatment initiation to death from any cause, whereas PFS was defined as the time from treatment initiation to either disease progression or death from any cause, whichever occurred first. Patients alive at the last assessment were censored on that date. Median follow-up was calculated using the reverse Kaplan-Meier method. Descriptive statistics were used to describe health care utilization, including ICU admission and unplanned hospital admission within 6 months of treatment initiation.
We used linear mixed-effects models with maximum likelihood estimation to account for missing data and to characterize PROs (FACT-Lym, ESAS-r, HADS) longitudinally across all study timepoints, treating time as a continuous variable. These models included fixed effects for time, along with random intercept and slopes. For QoL (FACT-Lym), we calculated the proportion of patients with improved, stable, or worsened QoL at 6 months and 1 year compared with baseline, with death considered worsened QoL. Symptoms of depression and anxiety were also transformed into dichotomous outcomes to reflect the presence or absence of clinically significant symptoms. We then calculated the proportion of patients experiencing clinically significant anxiety and depression symptoms at each timepoint.
To identify potential factors associated with QoL at 1 year post–treatment initiation, we first examined unadjusted associations between baseline variables and QoL at 1 year using linear regression models. The baseline variables included age, gender, diagnosis, race, marital status, education level, comorbidity score (CCI <2 vs ≥2),27 GA results (fit/unfit vs frail), VES-13 score (<3 vs ≥3), ECOG PS (<2 vs ≥2), elevated LDH above the upper limit of normal (ULN) (yes vs no), hypoalbuminemia (<3.5 g/dL),27 aa-IPI (<2 vs ≥2), lymphoma subtype (DLBCL vs high grade B-cell lymphoma with MYC and BCL2 translocations [HGBCL] vs mantle cell lymphoma [MCL] vs other), and treatment regimen. Variables were dichotomized based on prior literature or clinically relevant cutoffs. Variables associated with the outcome of interest at P<.10 were used to construct a multivariable linear regression model. To examine the association of treatment toxicity with QoL at 1 year post–treatment initiation, we evaluated associations between grade ≥3 nonhematologic toxicity (yes vs no), dose reduction (yes vs no), treatment interruption (yes vs no), and unplanned hospitalization (yes vs no) with QoL at 1 year using linear regression models, controlling for baseline QoL.
All reported P values are 2-sided, with P<.05 considered statistically significant. Statistical analyses were performed using Stata, version 14.2 (StataCorp LP).
Results
Patient Characteristics
Of 163 eligible patients, 106 (65%) were enrolled (Supplementary Figure S1, available online in the supplementary materials). One patient was excluded due to treatment with an ineligible therapy, resulting in a final cohort of 105 patients. The median age was 73 years (IQR, 64–99), with 42% of patients aged ≥75 years. One patient turned 65 years old after diagnosis but before treatment. Based on the GA, 40% were classified as fit, 10% as unfit, and 51% as frail. Additionally, 46% had a VES-13 score of ≥3 (Table 1). Full-dose chemoimmunotherapy was administered to 91%, 70%, and 72% of fit, unfit, and frail patients, respectively. Among patients aged <75 years, 95% received full-dose chemoimmunotherapy, compared with 57% in those aged ≥75 years.
Patient Characteristics (N=105)
| Characteristic | n (%) |
|---|---|
| Age, median (IQR), y | 73 (64–99) |
| Age ≥75 y | 44 (41.9) |
| Age-adjusted IPIa | |
| 0 | 15 (14.4) |
| 1 | 33 (31.7) |
| 2 | 44 (42.3) |
| 3 | 12 (11.5) |
| LDH >ULNa | 69 (66.4) |
| Albumin <3.5 g/dLb | 14 (13.6) |
| CCI score, median (IQR) | 1 (0–8) |
| Advanced-stage disease | 71 (67.6) |
| ECOG performance status | |
| 0 | 47 (44.7) |
| 1 | 40 (38.1) |
| ≥2 | 18 (17.1) |
| Self-reported race | |
| Asian | 3 (2.9) |
| White | 101 (96.2) |
| Not reported | 1 (1.0) |
| Gender | |
| Female | 37 (35.2) |
| Male | 68 (64.8) |
| Ethnicity | |
| Hispanic or Latino | 1 (1.0) |
| Not Hispanic or Latino | 101 (96.2) |
| Not reported | 3 (2.9) |
| Religion | |
| Atheist | 2 (1.9) |
| Catholic Christian | 41 (39.4) |
| Jewish | 13 (12.5) |
| None | 15 (14.4) |
| Other Christian | 25 (24.0) |
| Other religion | 8 (7.7) |
| Did not answer | 1 (1.0) |
| Relationship status | |
| Married/Living with partner | 76 (72.4) |
| Noncohabitating relationship | 2 (1.9) |
| Single/Never married | 3 (2.9) |
| Divorced/Separated | 10 (9.5) |
| Widowed/Loss of long-term partner | 14 (13.3) |
| Education | |
| ≤12th grade | 7 (6.7) |
| High school graduate/GED | 12 (11.4) |
| 2 years of college/Associate’s degree/Technical school | 27 (25.7) |
| College graduate | 25 (23.8) |
| Master’s degree | 23 (21.9) |
| Doctorate/Medical degree/Law degree | 11 (10.5) |
| Income | |
| <$25,000 | 12 (11.4) |
| $25,000–$50,000 | 13 (12.4) |
| $50,001–$100,000 | 30 (28.6) |
| $100,001–$150,000 | 17 (16.2) |
| ≥$150,001 | 25 (23.8) |
| Did not answer | 8 (7.6) |
| Lives alone | 25 (23.8) |
| Currently working | 23 (21.9) |
| VES-13 score, median (range) | 2 (0–10) |
| VES-13 score ≥3 | 48 (45.7) |
| GA category | |
| Fit | 42 (40.0) |
| Unfit | 10 (9.5) |
| Frail | 53 (50.5) |
| Histology | |
| DLBCL (de novo or transformed) | 74 (70.5) |
| HGBCL | 13 (12.4) |
| Mantle cell lymphoma | 11 (10.5) |
| Other histologies | 7 (6.7) |
| Treatment | 63 (60.0) |
| R-CHOP | 14 (13.3) |
| R-mini-CHOP | 10 (9.5) |
| R-EPOCH | 7 (6.7) |
| BR | 11 (10.5) |
| Other | |
| CNS prophylaxis | 14 (13.3) |
| Intrathecal chemotherapy | 11 (10.5) |
| Intravenous methotrexate | 3 (2.9) |
Abbreviations: B, bendamustine; C, cyclophosphamide; CCI, Charlson comorbidity index; CNS, central nervous system; DLBCL, diffuse large B-cell lymphoma; E, etoposide; GA, geriatric assessment; H, doxorubicin; HGBCL, high grade B-cell lymphoma with MYC and BCL2 translocations; IPI, International Prognostic Index; LDH, lactate dehydrogenase; O, vincristine; P, prednisone; R, rituximab; ULN, upper limit of normal; VES-13, Vulnerable Elders Survey-13.
1 observation was missing (N=104).
2 observations were missing (N=103).
Attrition and Missing Data
Rates of missing data for QoL are summarized in Supplementary Table S1. Nonresponders were more likely than responders to have a VES-13 score ≥3 (61.9% vs 35.5%; P=.044).
Clinical Outcomes
Among all patients (n=105 unless specified), 30.8% (32/104) experienced grade 3–5 nonhematologic toxicities, 22.9% (24/105) had dose reductions, 14.3% (15/105) had treatment delays, and 9.7% (10/103) had early therapy cessation. Overall, 7.6% (8/105) required ICU admission, 38.1% (40/105) had unplanned hospitalizations, and the treatment-related mortality rate was 3.8% (4/105). The overall response rate among patients assessed was 96.1% (99/103), with a complete response rate of 89.3% (92/103). At 6 months and 1 year post–treatment initiation, 95.2% (100/105) and 92.4% (97/105) of patients were alive, respectively. The median follow-up was 21.2 months (95% CI, 19.1–22.6). Median OS and PFS were not reached for the overall cohort or for patients classified as frail on GA (Supplementary Figure S2).
Longitudinal QoL
Longitudinal QoL significantly improved over time (β=2.77; 95% CI, 1.87 to 3.67; P<.001) (Figure 1). This improvement was observed regardless of age or frailty status (Figure 2). Among patients with data at baseline and 1 year (n=76), the median difference in QoL was 15.7 (IQR, −32.2 to 46.3) and the mean [SD] difference was 12.8 [25.1]. Figure 3 illustrates the proportion of overall and frail patients with improved, stable, and worsened QoL at 1 year. Among patients classified as frail on GA (n=34), the median difference was 8.5 (IQR, −13.4 to 29.0) and the mean [SD] difference was 6.1 [28.8]. Both of these mean differences exceeded the MCID. Among frail patients, receipt of dose-attenuated chemoimmunotherapy was associated with a higher probability of QoL decline compared with full-dose therapy (69% vs 31%; P=.041).
Longitudinal patient-reported outcomes. (A) QoL measured using the Functional Assessment of Cancer Therapy-Lymphoma (higher scores equal better quality of life); (B) physical symptoms measured using the revised Edmonton Symptom Assessment Scale (higher scores equal worse physical symptom burden); and (C) anxiety and (D) depression symptoms measured using the Hospital Anxiety and Depression Scale (higher scores equal worse symptoms).
Abbreviations: lb/ub, lower bounds/upper bounds; QoL, quality of life.
Citation: Journal of the National Comprehensive Cancer Network 23, 3; 10.6004/jnccn.2024.7082
Longitudinal quality of life by (A) age, (B) GA, and (C) VES-13 (higher scores indicate better QoL).
Abbreviations: GA, geriatric assessment; lb/ub, lower bounds/upper bounds; QoL, quality of life; VES-13, Vulnerable Elders Survey-13.
Citation: Journal of the National Comprehensive Cancer Network 23, 3; 10.6004/jnccn.2024.7082
Changes in quality of life 1 year after treatment initiation.
Abbreviation: GA, geriatric assessment.
aMissing 20% of surveys.
bMissing 21% of surveys.
Citation: Journal of the National Comprehensive Cancer Network 23, 3; 10.6004/jnccn.2024.7082
Longitudinal Physical Symptoms
Physical symptoms improved significantly over time (β= −2.12; 95% CI −2.72 to −1.52; P<.001) (Figure 1). Among patients with data at baseline and 1 year, the median improvement in symptoms was −5.5 (IQR, −19.5 to 3.0). Among patients classified as frail on GA (n=34), the median improvement in symptoms was −3.5 (IQR, −21.0 to 6.0). Both of these exceeded the MCID.
Longitudinal Psychological Symptoms
Longitudinal anxiety (β= −0.29; 95% CI −0.42 to −0.17; P<.001) and depression symptoms (β= −0.31; 95% CI −0.49 to −0.13; P=.001) significantly improved over time (Figure 1). Supplementary Figure S3 illustrates the rates of clinically significant anxiety and depression.
Factors Associated With QoL at 1 Year
Table 2 presents the results of univariate linear regression analyses. In a multivariable linear regression model, controlling for baseline QoL, being married/living with partner (β=11.6; SE=5.1; P=.026) was significantly associated with higher QoL at 1 year, whereas frailty on GA (β= −9.90; SE=4.6; P=.036) was significantly associated with worse QoL (Table 2). Hypoalbuminemia was excluded from the multivariable model due to its high correlation with frailty on GA and ECOG PS. Regarding toxicity, grade ≥3 nonhematologic toxicity (β= −11.0; SE=5.3; P=.043) and treatment interruption (β= −19.4; SE=8.3; P=.023) were both associated with worse QoL at 1 year, whereas dose reduction (β=0.30; SE=6.6; P=.963) and unplanned hospitalization (β= −7.9; SE=5.0; P=.118) were not significantly associated with QoL.
Factors Associated With Quality of Life at 1 Year
| Variable | β (95% CI) | SE | P Value |
|---|---|---|---|
| Multivariable analysis | |||
| Frail on GA | −9.90 (−19.2 to −0.64) | 4.64 | .036 |
| Married/Living with partner | 11.6 (1.44 to 21.8) | 5.12 | .026 |
| ECOG PS ≥2 | −10.4 (−24.5 to 3.75) | 7.09 | .148 |
| Baseline QoL (FACT-Lym) | 0.36 (0.16 to 0.57) | 0.10 | .001 |
| Univariate analysis | |||
| Frail on GA | −13.8 (−23.8 to −3.88) | 5.0 | .007 |
| Married/Living with partner | 13.0 (1.78 to 24.3) | 5.6 | .024 |
| ECOG PS ≥2 | −17.8 (−33.4 to −2.25) | 7.8 | .025 |
| Baseline QoL (FACT-Lym) | 0.38 (0.16 to 0.60) | 0.1 | .001 |
| Hypoalbuminemia | −27.7 (−47.9 to −7.41) | 10.2 | .008 |
Abbreviations: FACT-Lym, Functional Assessment of Cancer Therapy–Lymphoma; GA, geriatric assessment; PS, performance status; QoL, quality of life.
Discussion
To our knowledge, this is the first study to examine the longitudinal PROs of older adults receiving initial chemoimmunotherapy for aNHL. Approximately half of the patients in our study were classified as frail on GA, a proportion higher than that reported in previous prospective studies, highlighting the prevalence of frailty in this population.7,8 Despite this, patients in our study experienced significant improvements in QoL and in both physical and psychological symptoms with therapy, even those who were frail and very elderly. However, frailty on GA was associated with worse long-term QoL and more modest QoL changes, and patients aged ≥75 years showed relatively less improvement in QoL. These findings are important for patients and can inform clinician–patient discussions when initiating treatment.
We observed impressive improvements in longitudinal QoL and both physical and psychological symptoms with chemoimmunotherapy in older adults with aNHL. The median QoL difference of 15.7 exceeded twice the lower range of the FACT-Lym MCID, underscoring the substantial benefits of chemoimmunotherapy, even in older populations. In comparison, 2 prior studies of patients receiving novel treatments for relapsed/refractory DLBCL reported longitudinal mean FACT-Lym changes ranging from −0.9 to 10 points. Additionally, nearly 85% of patients in our study reported stable or improved QoL 1 year post–treatment initiation. These findings are reassuring and potentially instrumental in facilitating informed conversations between clinicians and patients about the risks and benefits of therapy. This is especially salient given prior research reporting that 17% of patients aged 65 to 74 years and 36% of those aged ≥75 years with DLBCL do not receive any treatment.28
Our findings regarding the longitudinal QoL trajectory in frail patients receiving initial chemoimmunotherapy are nuanced and have important implications. The fact that patients with frailty on GA experienced significant improvements in QoL—though at lower levels than the overall cohort—suggests that a portion of frail patients still benefit from treatment. Indeed, the increase in median QoL score by 8.5 is clinically significant, because it exceeds the lower range of the FACT-Lym MCID and is comparable to the mean change previously reported for responders to tisagenlecleucel 6 months after infusion.29 Therefore, frailty on its own should not automatically disqualify patients with aNHL from receiving treatment. However, our findings that frailty on GA was associated with significantly inferior QoL at 1 year, and that a quarter of frail patients experienced a decline in QoL, underscore the importance of supportive care interventions to enhance therapy tolerability, and suggest that additional novel therapies are needed to optimize outcomes in this subset of patients. Interestingly, QoL decline in frail patients was more common with dose-attenuated therapy, supporting that frailty on its own does not preclude full-dose chemotherapy and underscores the need for further studies to determine optimal dosing strategies for frail patients. In concert, these findings suggest that regular incorporation of the FIL GA in clinical practice could potentially improve care by identifying patients at risk for worse QoL with therapy and by targeting interventions to mitigate the risks of treatment in this population. Importantly, QoL decline could stem from disease or worsening frailty due to geriatric impairments. The FIL GA does not include domains such as social support, polypharmacy, and nutrition; thus, future studies should examine comprehensive GA in this population.
We also examined factors associated with QoL at 1 year. In contrast to frailty on GA, which was associated with poorer QoL, being married/living with partner was significantly associated with improved QoL at 1 year. This finding may be a surrogate for augmented social support, as prior research has shown that greater social support was associated with improved survival in patients with aggressive hematologic malignancies.30 Importantly, social support is a potentially modifiable factor. Interestingly, older age was not associated with QoL at 1 year, suggesting that age itself is not a robust predictor of therapy benefit. Grade ≥3 nonhematologic toxicity and treatment interruption were both associated with worse QoL, demonstrating the importance of mitigating toxicity and maximizing patient support during therapy. Due to the high response rate in our cohort, we were unable to assess the association of treatment response with QoL. Future studies should investigate whether supportive care interventions aimed at increasing social support in vulnerable older adults can improve clinical outcomes.
Our study has several limitations that should be noted. First, the patient population had limited geographic and racial diversity, potentially limiting the generalizability of our findings. Second, PRO nonresponders were more likely to have a VES-13 score ≥3, limiting our ability to fully evaluate the association between VES-13 score and longitudinal QoL, and introducing potential bias. Third, we excluded patients deemed inappropriate for chemoimmunotherapy, introducing an inherent selection bias. Fourth, our GA did not include domains such as social support, nutrition, and polypharmacy, which are critical factors that future studies should evaluate. Fifth, we evaluated toxicity using chart review, which could not fully capture toxicities. Sixth, the phenomenon of regression to the mean could explain some PRO findings. Finally, to maximize generalizability, our cohort was relatively heterogenous, and treatment dosing was left to the discretion of treating physicians. Future research should continue to evaluate longitudinal PROs in larger, diverse patient populations across multiple types of therapies.
Conclusions
In this cohort of older adults receiving initial chemoimmunotherapy for aNHL, patients experienced significant, clinically meaningful, and sustained improvements in QoL and physical and psychological symptoms. QoL improved regardless of age or frailty status; however, frailty on GA was associated with worse QoL at 1 year post–treatment initiation. These findings may inform clinician–patient discussions in the management of aNHL in older adults.
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